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AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection

, , , , and . Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, (2022)

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AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection, , , , and . Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, (2022)Distributed Data Storage in Support for Context-Aware Applications., , , , and . ISPDC, page 93-100. IEEE, (2013)A Spectral Approach to Unsupervised Object Segmentation in Video., and . CoRR, (2019)DATE: Detecting Anomalies in Text via Self-Supervision of Transformers, , and . Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, page 267--277. Online, Association for Computational Linguistics, (June 2021)Rethinking the Authorship Verification Experimental Setups, , , , , and . Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, page 5634–5643. Association for Computational Linguistics, (2022)Learning a Robust Society of Tracking Parts., and . CoRR, (2017)Learning a Robust Society of Tracking Parts Using Co-occurrence Constraints., and . ECCV Workshops (1), volume 11129 of Lecture Notes in Computer Science, page 162-178. Springer, (2018)Continuous User Authentication Using Machine Learning on Touch Dynamics., , , and . ICONIP (1), volume 9489 of Lecture Notes in Computer Science, page 591-598. Springer, (2015)